文章基本信息

标题：EXTRACTING PATTERN FROM LARGE DATA CORPUS USING APPROXIMATE REASONING AND INTUITIONISTIC FUZZY CLUSTERING TECHNIQUES
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作者：Dr. ASHIT KUMAR DUTTA
期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2019
卷号：97
期号：7
页码：2021-2031
出版社：Journal of Theoretical and Applied
摘要：The fuzzy logic is a familiar method to automate a complex activity. Intuitionistic fuzzy clustering is the extension of fuzzy logic. Approximate reasoning is a concept to deal vague and complex data. Many real time problems were solved with the help of Intuitionistic fuzzy concepts. Classification and clustering are the well known methods in the process of extraction of knowledge from the large data corpus. The existing techniques that are based on clustering methods could not provide optimum results with less computation cost. The efficiency of the existing methods was not up to the mark on large datasets. The objective of the proposed research is to provide an efficient technique for the extraction of meaningful pattern from large dataset with least computation cost. The proposed method has used the Intuitionistic fuzzy clustering technique with approximate reasoning for the extraction of pattern from the benchmark datasets. The experiment and results on large data corpus has proved that the level of the proposed research is satisfactory.
关键词：Fuzzy clustering; Pattern extraction; Pattern Miner; Fuzzy � C Means; Soft computing